(iii) Security and Privacy: Streaming private data onto third-party cloud servers yields privacy concerns from end-users, while weakly protected data streams can be exploited by cybercriminals. Federated learning [1]}, secure aggregation [2]}, and homomorphic encryption [3]} allow privacy-preserving and secure inference, but suffer from expensive network and compute requirement. On-board inference constrains the source and destination of private data within the IoT node itself, reducing the probability of privacy leaks and attack surfaces.
